Ask about this platform: capabilities, pricing, policies. Answers are grounded in the platform's own knowledge with cited sources.
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | The question, in plain language (max 2000 chars). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It does disclose the key trait that answers are grounded in platform knowledge and include citations, which is valuable. However, it does not mention any limitations, error handling, or the fact that this is a read-only operation (though implied). The disclosure is minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a concise two-clause sentence that front-loads the core purpose ('Ask about this platform') and then adds the grounding/citation detail. There is no wasted wording, and every part carries meaning. It is appropriately sized for a simple Q&A tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description covers the essential aspects: what topics are valid and that answers include citations. It does not explain the return format in detail, but for a Q&A tool this is acceptable. It could have mentioned that questions should stay within the platform's knowledge base, but that is implied. Overall, it is reasonably complete for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage for the single parameter, so the baseline is 3. The description adds semantic value by restricting the question to platform capabilities, pricing, and policies, and by implying that questions should be answerable from the platform's own knowledge. This goes beyond the generic schema description and helps the agent frame the question appropriately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('ask'), a resource ('this platform'), and scopes the topics to capabilities, pricing, and policies. It also distinguishes itself by noting answers are grounded in the platform's own knowledge with cited sources, which differentiates it from generic Q&A tools. Even without naming siblings, the purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for questions about the platform but provides no explicit guidance on when not to use this tool or which siblings to prefer. It does not mention alternatives like 'about' or 'quote', leaving the agent to infer routing based on context. This is a significant gap given the presence of sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool has a clearly separate role: about explains the platform, ask answers questions, list_actions enumerates available actions, quote creates an execution quote, and confirm executes or polls a quote. There is little risk of selecting the wrong tool.
The action pair quote/confirm and list_actions follow an obvious imperative style, and all tools are short and readable. Minor inconsistency exists because about is a preposition rather than a verb, and list_actions uses an underscore while the others do not.
Five tools is appropriate for this domain: discovery, informational context, quoting, and confirmation are all represented. The surface is compact without feeling thin.
The platform provides a complete workflow for agents: learn about the platform, ask questions, list available actions, quote a specific action, and confirm or poll it. There are no obvious dead ends in the core flow.